Design and practice of a platform for monitoring, early-warning and simulation of algal blooms in Lake Chaohu

近20年来，巢湖蓝藻水华频繁暴发，对流域内居民生活和社会生产产生了严重影响.由于缺乏蓝藻水华全方位监测、高精度模拟和智能化分析手段，传统方法难以实现现状掌握、异常识别、原因追溯、未来模拟的目标，无法满足巢湖蓝藻水华科学防控与应急处置的要求，蓝藻水华引起的突发事件随时可能发生.本文针对巢湖蓝藻水华的全面监测和应急决策问题，整合了卫星遥感、无人机监测、视频监控、浮标监测和人工巡测手段，构建了巢湖水质和水华全方位监测网络；结合巢湖水动力-水质-藻类耦合模拟模型，研制了蓝藻水华预测预警和蓝藻水华暴发应急处置模块，实现了蓝藻水华短期（未来2日逐时）和长期（未来7日逐日）模拟，并实现了未来5日蓝藻水华沿岸堆积模拟.最终，通过集成巢湖水质和水华监测、预测预警、应急处置等模块，研发了巢湖蓝藻水华监测预警与模拟分析平台，实现了全湖水质和水华现状迅速掌握、超标信息自动识别与高精度预测预警、沿岸重点区域水华堆积风险评估等功能，为巢湖蓝藻水华的科学防控和应急处置提供了科学依据和数据支撑.;Algal blooms occur frequently in Lake Chaohu recent 20 years, producing a serious impact on the resident life and social production watershed. Due to lack of effective means terms comprehensive monitoring, high-precision simulation, intelligent analysis, it is quite difficult for traditional methods achieve goal status mastering, anomalies identifying, causes tracing, trend simulating water quality algal blooms. Accordingly, requirements scientific prevention emergency disposal cannot be satisfied currently, emergencies caused by may at any time. Aiming monitoring decision-making blooms, network has been established Chaohu, integrating several means, i.e., satellite remote sensing, UAV (unmanned aerial vehicle) video buoy field monitoring. And modules prediction, early-warning response are developed combining coupled hydrodynamic-water quality-algal model. both short-term (hourly next 2 days) long-term (daily 7 simulations realized, as well simulation accumulation along coast 5 days. Finally, platform function modules, e.g., prediction early-warning, response, etc. By running this platform, present situation, exceding standard limits information, algae bloom whole lake can grasped quickly automatically, risk assessment key areas also realized. It shows that implemented provide basis data support Chaohu.